code: def inner(mode, pred, true_fn, false_fn, operands):
      if mode.enable_tracing:
          return trace_cond(
              mode, cond_op, pred, true_fn, false_fn, operands
          )
      else:
          return cond_op(pred, true_fn, false_fn, operands)
  
imports: from contextlib import contextmanager
  from dataclasses import dataclass
  import torch
  import torch._subclasses.functional_tensor
  import torch.fx.traceback
  import torch.utils._pytree
  from torch._C import DispatchKey
  from torch._C._functorch import _add_batch_dim, get_unwrapped, is_batchedtensor, maybe_get_bdim
  from torch._functorch.utils import exposed_in
  from torch._higher_order_ops.utils import autograd_not_implemented
  from torch._ops import HigherOrderOperator
  from torch._subclasses.fake_tensor import FakeTensorMode
  from torch.fx.experimental.proxy_tensor import disable_proxy_modes_tracing, make_fx, ProxyTorchDispatchMode, track_tensor_tree
  from torch.fx.passes.shape_prop import _extract_tensor_metadata
  from torch.multiprocessing.reductions import StorageWeakRef
  from torch.utils._python_dispatch import _get_current_dispatch_mode
label_desc: Use image node_id 6 for calling a global function with example usage: inner(mode, pred, true_fn, false_fn, operands) and returns: trace_cond, cond_op